The genome hasn’t failed

On Monday, the Guardian published an article by plant geneticist Jonathan Latham entitled “The failure of the genome”. Ironically given this is an article criticising allegedly exaggerated claims made about the power of the human genome, Latham does not spare us his own hyperbole:

Among all the genetic findings for common illnesses, such as heart disease, cancer and mental illnesses, only a handful are of genuine significance for human health. Faulty genes rarely cause, or even mildly predispose us, to disease, and as a consequence the science of human genetics is in deep crisis.

[…] The failure to find meaningful inherited genetic predispositions is likely to become the most profound crisis that science has faced. [emphasis added]

We suspect for most of our readers Latham’s rather hysterical critique will fall on deaf ears, but it is part of a bizarre and disturbing trend that needs to be publicly countered. Here are several of the places where Latham’s screed gets it patently wrong:

Complex disease genetics ≠ all human genomics.

This article, and many like it, poses the issue as a general failure of human genomics, but then proceeds to critique only one sub-field: complex disease genetics, the study of multifactorial diseases such as type 2 diabetes and heart disease. Complex disease genetics is in some ways an easy target: in its most modern form the field is only four years old, with its birth dating to the first genome-wide association studies (GWAS) published in mid-2007. In that time the field has uncovered an astonishing number of (independently replicated) genetic variants associated with human disease, but our understanding of the genetics of complex traits is still in its infancy.

Yet Latham and his ilk allow their sniping at complex disease genetics to ricochet off into the broader field of human genomics. Whatever you feel about the success of complex disease genetics, proclaiming “the failure of the genome” does an indisputable disservice to the areas where genetics has made a huge difference both to science and to the lives of patients: for instance, the unravelling of hundreds of severe inherited diseases, and major advances in our understanding of the biology of cancer.

We’ve found plenty of validated genetic variants associated with common diseases

Latham states flatly: “The most likely explanation for why genes for common diseases have not been found is that, with few exceptions, they do not exist.” Yet “genes for common diseases” certainly do exist, and (as noted above) they have been found in vast quantities over the past four years.

These associations are not false positives. They have been found in enormous studies (frequently including tens of thousands of disease patients) looking at hundreds of thousands of markers throughout the genome, and systematically, independently replicated in separate populations using stringent statistical approaches. We have learnt orders of magnitude more about the genetic basis of common diseases in the last four years than we learnt in all of the preceding decades.

Latham could focus his criticism on the effect sizes or predictive utility of the discovered variants; there are reasonable points to be made here. However, instead he chooses to cast his net far too wide, dismissing complex disease genetics entirely with a rhetorical flourish. This is a contemptible manoeuvre.

Even for complex traits, the genetic variants discovered are already more predictive than many environmental risk variables

Latham argues that there has been a “failure to find meaningful inherited genetic predispositions” for common diseases. He is wrong for any reasonable definition of “meaningful”. For most common diseases, while the majority of genetic risk remains hidden, we have uncovered an appreciable fraction of the inherited risk (typically 10-20%) using a single technique (GWAS). This fraction is non-trivial – in fact, the genetic variants uncovered by GWAS frequently explain more of the risk of these diseases than known environmental risk factors.

For weakly genetic diseases, such as type 2 diabetes, known genetic factors account for around 2% of the variance of the disease. Compare this to 1% for smoking, and 9% for body-mass index. For more strongly genetic diseases we can do far better. For Crohn’s disease, a form of inflammatory bowel disease, newly discovered variants can explain around 12% of variance, compared to 3% for smoking (the strongest measurable non-genetic predictor of life-time risk). The biggest success story of the new breed of genetic studies is age-related macular degeneration, a common eye disease, for which recently discovered genetic variants can explain around 50% of variance in disease risk.

[By way of method, in each case I’ve calculated the percentage of risk variance explained using the method laid out by So et al earlier this year. -LJ]

The assumptions of twin studies have not gone untested

Out of necessity for this argument, Latham attacks twin studies, one of the primary methods used to establish to genetic component of nearly all complex diseases. We do not want to shoot down discussion of the potential pitfalls of twin studies, as there are many, and there are important discussions to be had about them. Not enough people understand their methodology, and fewer still dig deeper into the subtle effects that can influence their heritability estimates. Unfortunately, Latham is not on the side of the angels in this matter; when we wrote about his last post, we noted that he had made an embarrassing error betraying his lack of understanding of the methodology, and while he manages to not make as many egregious mistakes this time around, his treatment still fails to grasp the issues.

The twin study methodology is simple, but it does make a number of assumptions. The one that Latham cites is that the environments of identical twins are about as similar as the environments of non-identical twins, but they also assume that genetic risks combine together in a simple way. However, in no way have these assumptions been “swept aside and all but forgotten”, as Latham claims; in fact, they have been carefully tested. Large reviews of twin studies themselves show that there is no large, systematic deviation from the assumptions. In addition, comparisons of heritability estimates with independent, non-twin-study methods show no systematic differences; these methods include old ones like siblings-reared-apart studies, and newer methods such as sibling identity-by-descent sharing, which are notable for getting around all traditional criticisms of twin studies by directly measuring the genetic relatedness of siblings. If dominance or identical vs non-identical twin differences were interfering with our estimates of heritability, and the assumptions of twin studies were being violated, it would have shown up in these studies.

Fully explaining disease risk is not essential to provide insight into disease

Lathan makes a fundamental error when he equates explaining disease risk and understanding a disease. We could understand all the factors that predispose individuals to a disease, and yet learn nothing about it. Likewise, even small risk factors can shed important light on complex diseases.

As noted above, the genetic variants discovered so far explain only a fraction (albeit a useful fraction) of complex disease risk. However, the usefulness of this research far outweighs the risk it explains; it gives us a database of regions of the human genome that are involved in each disease, containing a range of genes with a variety of functions, each of which we can then investigate biologically. This sort of research has uncovered new mechanisms involved in a range of diseases: for instance, the previously unappreciated importance of a biological process called autophagy in the etiology of Crohn’s disease, and the role of lipid metabolism in Alzheimer’s. The better we understand the mechanism of disease, the more likely we are to be able to identify drug targets for pharmaceutical intervention.

There’s no need to hype the results here: this doesn’t mean that cures for all common diseases are just around the corner. However, without an understanding of the biological pathways that underpin human disease, drug development is little better than random chance, and GWAS have unquestionably provided novel insight into these pathways.

69 Responses to “The genome hasn’t failed”

Thanks so much for this. I was traveling this week and hadn’t seen Latham’s Guardian item.

This looks so much to me like the anti-vax methods that it makes my head asplode. I think we are seeing the beginning of strategy that could eventually lead to the same kinds of public health issues that anti-vaxxers have generated.

This is important to monitor. I’m seeing it spread among the alt-med community in various ways. Thanks for taking it on.

Lovely article, and a perfect antidote to the tedious hand-wringers who have never understood genomics and never will. We are on the brink of big things; the HGP was planting the seed. Soon we will reap the harvest, and personally I have a lot of confidence that a significant chunk of the “missingheritability” will cascade out of the Next Generation Sequencing analyses. Lots and lots of rare variants, rather than a few common variants. In other news, they are slagging off Columbus for not discovering the Grand Canyon…

Any confused readers who think these criticisms of our work amount to more than a hill of beans need to read a) Dermitzakis E.T. and Clark A.G. (2009) Life after GWA studies. Science 326: 239-240 (this one is short and clear and accessible to anyone) and b) Manolio T. et al. (2009) Finding the missing heritability of complex diseases. Nature 461: 747-753 because if we are wrong so too are they. Only a tiny handful of important genes for common diseases have so far been found. That’s what Manolio et al and Clark and Dermitzakis say and so do we. The question now is why is the public not being told this and whether the search is worth continuing. yours sincerely

Both of those articles are reasonable articles discussing the large proportin of genetic variance yet to be found. They discuss strategies for finding them, and experiments that can be going on in the future. I would strongly recommend that people read them too, so they can see how little they support your argument.

Neither of them support your assertion that the complex traits do not have a significant genetic component, or that genome-wide association studies were a wasted effort.

You need to start actually address people’s criticisms of your ideas, rather than giving nonesense arguments, and when they are attacked producing papers that do not support what you are saying and then shouting “LOOK! THESE PEOPLE BELIEVE WHAT I DO!”

We would also encourage readers to explore both of these works (available here and here, for those with journal access).

Both articles argue much the same points that we raise above: that we are still in the infancy of understanding the genetics of complex diseases, and the associations we have identified so far still have very limited predictive value, but what we have uncovered so far has nonetheless been valuable.

Far from arguing that “[o]nly a tiny handful of important genes for common diseases have so far been found”, Manolio et al. say:

In the past few years, [genome-wide association] studies have identified hundreds of genetic variants associated with such conditions and have provided valuable insights into the complexities of their genetic architecture.

And Dermitzakis and Clark note, regarding the biological value of the associations collected so far:

The explosion of genome-wide association (GWA) studies has expanded the set of candidate genes and genomic regions for future study. Examples include underscoring the role of immunity in macular degeneration, and shifting the emphasis in type 2 diabetes risk from genetic factors affecting insulin resistance to those that influence insulin production.

I also note that neither Manolio et al. nor Dermitzakis and Clark make any of the more ridiculous arguments proposed by Latham: neither article argues that human genetics is in crisis, but instead both note that our current understanding is incomplete and propose the way we should proceed with the next wave of experiments. To argue that these articles in any way support Latham’s central thesis (that common disease risk is fundamentally non-genetic) is absurd.

Come on Jonathan, hiding behind the ‘if we are wrong then so are they’ argument don’t explain why you’re right. In fact, even one of the articles you cited mentioned this: ” The nearly 400 GWAS published so far represent a wealth of data on the genetics of complex diseases. These studies have provided valuable insights into the genetics of common diseases, particularly about the underlying genetic architecture of complex traits and the predominance of non-coding variants that may have a role in their aetiology. ”

and in your article you wrote this: ” The failure to find meaningful inherited genetic predispositions is likely to become the most profound crisis that science has faced. ”

So your article is not exactly going on the same line with those two you mentioned.

I think the authors of this blog post has made a sensible rebuttal to your Guardian piece. You’re playing too much on big words; claiming the whole field of genomics has failed. It is indeed a problem that we haven’t known how far genetics contribute to common diseases, but it does not mean the whole field failed. In fact, it means that we need more resources and effort in the field.

Using 34 established loci for diabetes risk, each with a very small contribution, the study showed it was possible to improve predicition of type 2 diabetes. More importantly they also showed that for the significant numbers of subjects who became glucose intolerance in this large prospective study, the various interventions to return them to normal glucose tolerance were much less effective in the higher genetic risk group.

What this is saying is that for the genetically higher risk group (detectable while healthy of course) – it would be a BAD idea to wait for traditional risk factors to appear before intervening because reversal is more difficult.

This is a follow-up and confirmation of previous work – it is only a few years since GWAS have been discovering these loci, in my opinion this represents a real success and a clinically useful tool.

No the genes don’t cause the disease, nor do just the environmental factors – knowing one you can have better control over the other. But this is so obvious, so clearly demontrated I don’t really understand the Latham type of position, what’s it all about????

@Keith: Latham has an agenda. He wants the problems to be all environmental, so that people have to eat all organic foods, and reduce all exposures to teh toxins, ban GMOs, and so on. His report (that some people mischaracterize as a study that has been peer-reviewed) has been picked up by people who are selling detox garbage on Huffington Post, and also by people opposed to GMOs, and that sort of stuff–people who are finding him to be a useful idiot to drive their detox tea sales or raise funds for their environmental agenda.

it all seems a bit paranoid anyway – i don’t see many in the genomics world saying that it’s all in the genes. The genetics interact with the environment – of course the environment is important, it’s not either / or (strange that some on both sides seem to think that).

I think the genome basher some times score points. I commented on Latham’s views as presented in The Guardian on The Daily Scan blog of the Genome Magazine. I would like to post it here:

On the “30 years of DNA” Nature conference held in 1983 Leroy Hood said, it will take ~20 years to get a genome draft and ~100 years to understand how changes in the genome cause disease. So it’s no wonder the educated public and scientists do not understand how genomic changes cause disease. Moreover, many scientists do not understand the concept of causality, using meaningless terms like “associated, linked etc. Besides in addition to protein coding genes that are well defined and easy sequenced (exom sequencing) the genome contained a large number of functional RNA genes (mirnas, large ncrnas and other less defined species), which harbor changes causing pathology. On a positive side most if not all cancer causing gene mutations are identified and are useful in a clinical setting (diagnosis and treatments). Another problem affecting science itself is excessive hyping that permeates every paper, every presentation. Hyping scientists should be punished and not get funding. Michael Lerman

I think it’s important to distinguish between the science and the selling of the science. IMHO, it’s silly and a non-sequitur to argue that GWAS were a waste of time–we had to do the experiment and we did. Were the results disappointing from a human health standpoint? Absolutely. But the “fail” is not in our genomes, it’s in ourselves, i.e., the hype that began in the 1980s and promised us a medicine cabinet full of genome-derived drugs and “our children’s children not suffering from cancer.” Even if GWAS had succeeded wildly, the results would still not have matched the extravagant claims made by many in the genome-industrial complex circa 1999.

Misha makes a wonderful point. This discrepancy runs far and wide – even as far as NIH funding trends. GWAS continues to provide valuable information. And at a minimum, the big drive in GWAS technology competition has lowered the prices for micro-array chips so that our newly beloved, and relatively small sample-sized, sequencing projects can be augmented by targeted custom array chip-based studies on the cheap.

A new approach to understanding the effects of the complexity of our genetic make up is healthy science. Crisis exists when incredibly qualified people are no longer satisfied with pursuing discovery through proper scientific method and either quit, nay-say, or get unethically creative.

Unfortunately, it seems the “hype” is what is necessary to get funding in the first place. I was taught in graduate school that when writing a grant proposal, if “no one is dead or dying by the second sentence” you won’t get funded — the old “blah blah has been implicated in cancer” or “X millions of people die of Disease every year” — and the conclusion usually brings it back full circle to how the project will help solve that problem. I was working at the computational level and we still wrote like that.

So don’t punish the scientists –the funders themselves are exacerbating the problem. Then you also have to acknowledge that legislators and taxpayers aren’t going to allocate funding for “boring” science. Who would want to put public dollars into research “elucidating the mechanisms underlying protein A inactivation by protein B”? People want to know how it’s going to cure cancer. Same goes for what they want to read in the news. I can’t say I can blame anyone, really.

It seems to be accepted without question that there really was a lot of over hype before the human genome project, and when it was finished a) to fund the project then b) to fund the GWAS (and probably it should be happening now to fund WGS)

Was it really so over-hyped? Some people probably did over-hype it, who were they and how many?

I’m not saying it wasn’t but it would be good if some investigative person out there could do a bit of searching and catalogue the extent of it all, maybe the amount of hype has been exaggerated?

Sure, in grant applications you need to put a positive spin on things. Often you have to answer specific questions like “What will be the benefit to society of this project?” and when we say things like “learning more about the fetal epigenetic profile during gestation could lead to world peace…” we don’t really mean all of it and we know that on the other side the reviewers tend to recognise and ignore these things anyway (I do at least).

Overhyping would have to mean making exaggerated claims in a public forum which end up in the mainstream press and make it easier to fool politicians into funding GWAS or whatever. So was there? Obviously Latham is guilty of it in his various scribblings, but were others from the molecular biology world?

Shirley is right: funders are obsessed with “translation” and “broader impacts.” But it takes two to tango. Reviewers and applicants come from the same pool. If they resist the urge to hype then I would like to think that the culture can start to change.

And Keith, I have a whole series of PowerPoint slides full of quotes from genome luminaries circa 1989-2005 telling the world how great it was all going to be. There is plenty of data.

I actually heard with my own ears a genome project manager in a small country saying that we will find hundreds of new cures thanks to the genome project within a decade. This was in a layman talk (nurses), but this guy KNOWS how long it takes a drug to reach the market. So I tend to attach some of the blame on scientists hyping the field.

Just finished reading today’s editorial in JAMA, “Whole-Genome Sequencing-A Step Closer to Personalized Medicine by Boris Pasche, and felt my continued excitement about genome sequencing today. Really does not mesh with Latham’s “genetics in a crisis” and genome sequencing “not worth it”.

Just ask the family who can now test members for their one off mutation in Pasche’s first example or the clinical diagnosis that only whole genome sequencing could do in the second example.

Whole genome sequencing is making a big difference to people’s lives right now. We need the sequencing and the informatics to be cheaper/faster/better of course but we can pull off some remarkable personalized medicine success stories that fix people right now.

I am a genomics tools sales specialist and have been for the last 20 years. Here is my take from a completely different angle. I have never seen so many scientists buy totally unnecessary random toys to sequence completely useless material. I have seen labs over this time born and die of a slow idiotic life because they laid out the most ridiculous massively parallel studies with very poor managerial attributes. So many millions lost. This may not be news and of course has been feeding me and my billionaire visionary pompous boss who thinks we will all have a sequencer in our garage… Even today, I still see labs buying sequencers with little or no bio-informatics background or see amazing AACR data being bombasted to reality: http://blog.fejes.ca/?p=551 and many more in that blog.

Scientists need to understand they are simply weak at being small business entreprenor rather than real scientists.

I will continue to believe, to this day, that drugs are not the solution, fat is not good, yes petroleum is nasty and so is a bad environmental. I still believe millions still die from unfit water, AIDS and malaria. I still believe that a simple tape measure and running shoes will save more lives than any NGS device. Finally I still believe that hardly a single genetic finding as come full circle to truly evaluate its clinical cost of return… If scientists keep asking for money on such little delivery, they are the ones crying for money and making unrealistic promises to society, Francis Collins is Jesus, until the US go bankrupt… This is unfortunate, I think science should win, I think genomics has its place but not like this, not this way and your sirs are to blame for the reality you have enclosed yourselves into.

Keep digging your heads in the sand as we come near the third genomic bubble of uselessness. The only problem is this time, journos will be romancing it and scientists will be quoted and the population at large will take note. Good luck on your fourth bubble as I will be retired after taking money from scientists who will have done very very little to change my health.

I know this is nasty to hear but until genomic science stops overstating and start delivering, I suggest some of you have the decency to look at the billion thrown at research and STFU… Even cure has become a dreadful and machiavellic corporation…

Paul, come on, the example in JAMA is ridiculous ! First of all, in many cases, it’s often been shown the WGS just gave them a few tracks to follow for some very rare diseases, the statistical value of this is ridiculous, this is about common disease trait. You want to have the argument on pharmacogenomics also ? Funny, I thought there was a hearth attack prediction gene out there and a mutation for certain statines. Ho wait, let’s call for a budget were we do a complete and full body scan for everyone at the age of 40. Let me go get a colonoscopy where I know for sure, absolutely guaranteed that I will have a polyp (who cares, I will die one day, if not from that damn polyp, it will probably be from my god damn prostate… come one people let’s invest where it makes sense to invest). In the meantime, I was told by 23 and me that I have hypercholesterolemy and I just can’t hold back on that Double Down…

Elmatos, while those posts are strong on passion, they are weak on coherence. I am a clinical geneticist, and I deal with hundreds of families every year where the genome very much *has* delivered, and keeps delivering. We would not currently have NGS devices/services (is the distinction even relevant any more?) were it not for the human genome project, and by the sound of it you wouldn’t even have a job! Think of a lot of this research money as stimulating/subsidising the development of a new industry sector. Your boss has it all wrong if he thinks everyone will need a sequencer. What we *need* is the *sequence*. Your genome is essentially a big chunk of data (actually not that big – just over a CDROMful) that you could as easily carry around on a USB stick or upload to a server. NGS is simply a way of getting past a firewall set by biology.

But that is what this is all about – it is not about “finding cures in the genome” (I really don’t think anyone working in the field for the last 20 years has been anticipating this, despite the breathless hype of the journos). It *is* about understanding the *biology*, and that is paying off in spades. We are finding out how the human organism functions. Genes are not “magic”, nor are they “building blocks”, and they certainly aren’t “for” anything directly. But thanks to our developing understanding of the genome(s), we are putting together some very powerful explanatory frameworks for getting to the bottom of the biology of disease.

Now, I’m a clinical geneticist, yes, and I don’t have a heck of a lot to offer my patients other than a diagnosis and the phone number of another family facing the same situation (actually, I underplay my hand here – there is often a lot we can do, and this is improving all the time). But when you tell the parents of a 20 year-old girl with severe learning disability and epilepsy that she has a de novo mutation in TCF4 and a diagnosis of Pitt Hopkins syndrome, after a lifetime of the mother blaming *herself* for causing this, and panicking over the possibility of it being transmitted to her other children’s children, then you see that knowledge itself is of real therapeutic value.

And so the feck what if the diseases are “rare”? Rare diseases are the natural experiments by which we have unpacked a phenomenal amount of human biology that is directly relevant to “common” diseases. Furthermore, there are more people collectively with “rare” disorders than there are with most “common” conditions. And as if that weren’t enough, “rare” disorders are almost invariably more common than you realise, and “common” disorders are almost invariably rarer.

Genomics is helping us to break down that firewall and manage genetic information in much the same way as other digital information; sure, we need to know how to interpret it, but we are not nearly as ignorant of its import as many people (such as Latham) imply, and, perhaps more importantly (and fatal to the doom-mongers’ lamentations) there is no sign of this slowing down. The advances are real, and they are delivering *now*, just perhaps not in the way that some people in their simplistic and medically uninformed analyses wanted them to.

@ elmatos: considering the field (of GWAS) is only 4 years old the progress is staggering. Consider that whilst the ORs of most SNPs are small, they still nevertheless indicate some association between specific DNA regions and phenotypes that can be used, for example, to fine tune epigenetic studies of those regions and are therefore potentially useful signposts. I think we need to stop thinking of the genome as less of a blueprint and more of a recipe book – with (epigenetic) annotations based on environmental exposure.

Keep promising, it’s entertaining, I have yet to read an inch of remorse on some of these ridiculous claims. Shame on us scientists for pushing cure like dope dealers.

I think I sold my Decode shares just at the right moment…

Reminder: America is dying of early onset diabetes because it is fat.

Submitted by lermanmi on Mon, 04/25/2011 – 18:26.

I commented here and at at Genomes Unzipped on Latham’s views before.

As i said the real problem underlying the argument of genome bashers is excessive hyping that permeates every paper, every presentation. Hyping scientists should be punished and not get funding.

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Good point, I heard Kerry Submitted by Azzy7 on Tue, 04/26/2011 – 09:44.

Good point, I heard Kerry Mullis speak and he spent a large part of the time bashing the NIH/NCI and the hype around solving the gene map and the obviously false promise to cure cancer by 2015. He likened it to the story of the boy crying wolf and the public would turn on us. It looks as if some scientists are also turned off.

[wiki] NCI Director’s ChallengeIn 2003, Andrew von Eschenbach, the director of the National Cancer Institute issued a challenge “to eliminate the suffering and death from cancer, and to do so by 2015”.[10][11] This was supported by the American Association for Cancer Research in 2005[12] though some scientists felt this goal was impossible to reach and undermined von Eschenbach’s credibility.

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The human genome had to be Submitted by captaindory on Tue, 04/26/2011 – 11:48.

The human genome had to be sequenced but the taking over of funding is what concerns me, even as an ex-researcher. What percentage of the NIH budget goes for genome and genomish studies such as GWAS, signature studies, micro array analysis and proteome analysis as compared to other research? It seems like those studies are done and left to die, rarely benefitting anyone or further examined. True of much research even before the genome explosion. There is a lot to be gleaned, but no one, except the systems analysis folks, who have their own hype to promote, has the time to read enough and put 2 and 2 together.

Meanwhile, Joe Average has trouble getting basic healthcare. Little wonder then that there is public skepticism regarding genomics.

Not that I don’t think that genomics research isn’t essential, but effective drugs for many common illnesses are years away. Meanwhile, there is drastically inadequate spending on known remedies for common illnesses.

I recently went for an in depth cardiology screening at Stanford University. (My family has a strong family history of heart disease.) For less than a thousand dollars, you can have an in depth risk assessment and lifestyle counselling for heart disease. Do we do this across the population? No, even when it is our number one killer. We’re left with banal blood pressure and cholesterol level checks that cover only a subset of risk factors.

If we can’t afford screening for our number one killer, heart disease, I doubt that we can afford individual genome sequencing, whole genome counselling, and follow up testing across the population.

The end game for the cost of personal genome sequencing, vis a vis population wide screening and preventive care hasn’t been thought through.

Marny, thank you for eloquently saying this. Thank you so much. I scientists who can’t get enough toys for the lab, read it, over and over.

Again, my interest is for a sequencer looking at every door knob of an airport at every minute of the day (the funny dream of Pac Bio as an example). I want to be a millionaire… but after all these years, I have become jaded but healthier than ever by just laughing at the ridiculous claims…

I would like to point out the great disservice that Jonathan Latham is doing to the Bioscience Resource Project, and his colleagues who work there. Their stated aim is to provide “independent news, commentary and information for the agriculture-related biological sciences including biotechnology, ecology, plant biology and food science” in the service of a “biodiverse, sustainable, just and peaceful” future. By engaging in tactics typical of climate deniers and creationists, and then linking back to the Bioscience Resource Project home page, he not only undermines his immediate concern (that heritability is overestimated, genetic determinism is ascendant and the genome is oversold — all points that could have been legitimately made) but he also damages the reputation of his entire enterprise.

The problem in comparing the environmental and genetic variance is not that the environmental variance is necessarily much bigger than is already known (although it may well be), but that the two preventive health strategies (genetic ‘prediction and prevention’, or population based) are entirely different. The environmental variance is related to the population attributable fraction i.e. the proportion of cases that could be avoided by removing the exposure. But the equivalent population attributable fraction for genetic factors is meaningless because we cannot remove the genetic factors. Instead we need to look at the proportion of disease that could be removed by reducing exposures or giving medication to this ‘high genetic risk’ group. In general, this reduces the benefits of the environmental approach (by restricting it to a high risk group) and increases the preventive use of medication: this is good for big pharma and the food, tobacco, nuclear and chemical industries that have promoted this health strategy, but it’s expensive and (generally) not good for health or not very effective or cost-effective at reducing disease incidence. Some example calculations on population attributable fractions (PAFs) are here: http://www.tbiomed.com/content/3/1/35

The PAFs are inter-linked with the question of heritability because there are always trade offs: e.g. if the G-E interaction goes up so does the utility of gene screening but the calculated heritability goes down; a highly predictive genetic test will tend to identify only a small proportion of disease, but a test that captures a high proportion of disease incidence tends to have low predictive value. None of this undermines the potential of GWAS to be useful in other ways (i.e. identify disease mechanisms etc.) or the value of genetic testing (and sometimes whole genome screening) for genetic diseases and familial forms of diseases etc. But it limits the benefits of the idea of genetic ‘prediction and prevention’ of common diseases in the general population. Why does this matter? Because it’s not just science but also about policy and the messages being sold to the public and politicians. The history of how and why the tobacco industry funded the genetic ‘prediction and prevention’ approach is here:http://www.hss.ed.ac.uk/genomics/documents/Vol5No1.pdf

You will note Sydney Brenner’s secret meeting with the tobacco industry a month before he set up the Human Genome Organisation. The problem is not just hype but deliberately misleading industry-funded attempts to promote the idea that the future of disease prevention requires personalised genetic screening and individualised advice will be more effective than a crack down on the marketing practices of the tobacco and fast food industries etc. Do not be naive. You got to do your science but a price was paid.

your comments have nothing to do with what Latham was claiming, i.e. that genetics are not very important for complex disease, and all the “genetics is in deep crisis” nonsense. You appear to have started a new conspiracy theory thread (new as in thread, the conspiracy stuff is all old hat) which does not really involve genetics at all – there are plenty of “food & tobacco etc industry is evil” sites which would be more appropriate.

You miss many points anyway. I don’t read many (any?) articles pushing mass genetic screening for population based health strategies – despite our naiveté most seem to agree that it’s too early for that. It’s also called “personal genetics” for a reason.

“a highly predictive genetic test will tend to identify only a small proportion of disease” – why? Soon we may have highly predictive tests that will identify 80% of those who will develop type 2 diabetes IF they allow certain environmental influenced risk factors to go over the thresholds (BMI, waist circumference, exercise levels, etc).

There is a simple genetic test (determination of skin colour) that predicts almost all cases of skin cancers in people who do not protect themselves adquately. Population based healthcare strategies designed to reduce the incidence of skin cancers actually incorporate genetics, and personalised products are routinely used (sun screen lotion) – and have been very successful. In the future the same will be the case for many other complex diseases – unless the research stops now. The genetics will be used for population healthcare, but will cure nothing, it will still depend on the population members to take the appropriate protective measures.

I don’t see how any of this will help the bad food industry – on the contrary. It’s true it has helped “big sunscreen” but that a good thing I would think – no?

A quick note – as an author of this post, I am perfectly happy for Helen to bring up topics like this, providing she does it in a sensible way (which I believe she has). Her points about the different ways you handle environmental and genetic risk are good, and worth bearing in mind.

The thread has pretty much run its course anyway, and if people want to discuss the societal impacts of genetic screening and genetic research, and their relationship with finanial interests like pharmaceutical companies (which afterall have both a great potential to help and a great potential to harm public health), then I think GNZ is a good venue for that.

@Luke – sure but my point about being off topic is that the aim is to minimise the use of genetics. I agree that there are sensible parts to the post, if it had stopped there it would have been fine.

But to then go on and imply that the whole Human Genome Organisation was set up by Sydney Brenner to help the tobacco industry, and to suggest that the population has paid a heavy price for the funding of genetics research is not so sensible.

I think we actually agree on a lot of things. While I’m not at all sold on the human-genomics-as-big-tobacco-conspiracy theory, I certainly agree that greater investments in understanding and mitigating environmental risk factors are warranted. Given a finite healthcare budget and expensive/invasive interventions, some level of risk stratification will be essential for at least some diseases. However, I agree that this doesn’t in any way eliminate the need for greater research into the effectiveness of broader environmental interventions.

Even as a direct beneficiary of money thrown at medical genetics over the last five years, and someone who blogs entirely about news in the genetic domain, I freely acknowledge that these criticisms have merit. Genetic dissection of common disease is valuable, and will be (and indeed already has been) fruitful in generating new therapies, but it is nonetheless true that research into environmental risk factors and interventions to minimise morbidity is woefully under-funded and under-reported relative to its potential benefit.

This article could thus have been a considered, balanced and valuable critique of the imbalance in funding between research into the genetic and environmental contributors to common disease. Instead, the authors have undermined their argument by wandering into territory they don’t understand, and taking an extreme position that is inconsistent with the available evidence. Perhaps they felt that polarising the debate was the only way to get attention – and indeed that approach seems to have worked – but that has come at the cost of destroying the credibility of their message. This was a missed opportunity. [emphasis in original]

Marnie and elmatos and Latham and all their ilk are typically shortsighted. They are like the people who thought Al Gore was full of hot air when he spoke about an information superhighway in the late 80s.

Change is overestimated in the short run and underestimated in the long run.

Give us the hypemeisters of the internet boom over dismal Malthusians like Latham who spend half their time blocking progress and half their time asserting that said progress is impossible. For the hypemeisters were actually right in the long term: we really do now have that “convergent” device promised in the 1990s — the one which can pull up just about any movie, song, or document in the world with a few taps, wirelessly.

It’s called an iPhone.

What Marnie et alia don’t get is that the kind of people who write big checks don’t usually fund entrepreneurs who are proposing things that are incompatible with basic physics. Those early entrepreneurs might be ahead of their time (AOL operated for 7 years before becoming a goliath), but they usually aren’t wrong about *technical* feasibility.

So on a purely technical basis, let’s bring this whole conversation back down to earth: you just can’t argue with the fact that the cost of sequencing has dropped at a supra-exponential rate. The remaining obstacles to getting the genome out there are man made, NOT technical. There are plenty of things you can use sequencing for that do not involve solving the missing heritability problem, but humans — not physics — are stopping us from achieving them.

To understand this, first know that it used to be illegal to use the Internet for commerce. Here’s Steve Case, founder of AOL:

The first was a research phase (the 70s) where some forward thinkers were working on early research projects for what was then called videotex, teletext, 2-way TV, etc These were experiments in labs as consumers did not have PCs or any practical way to access these services. Futurists like Alvin Toffler wrote about the notion of an “electronic cottage” (he wrote The Third Wave in 1979) but it was considered a pie-in-the-sky prediction.

Next was the pioneering phase (early 80s to early 90s) where a relatively small number of people were trying to build interactive services, but it was an uphill battle. Few people used them (and the Internet itself was still limited to government/educational institutions – indeed, it was illegal to use it for commercial purposes.) The conventional wisdom was that the market would always be limited to hackers/hobbyists. AOL was the first “Internet” company (it was actually called an “online services” or “interactive services” company at the time) to go public and I remember on the road show (in 1992) explaining why we thought this would be a large market someday. Given we had been in business 7 years and had less than 200,000 users, most were skeptical.

Amazing, huh? This sounds so arcane and bizarre that it makes you scratch your head in wonder. Isn’t the internet synonymous with .com’s, after all? How could there possibly be a time when this wasn’t the case? And would people be so blind as to put man-made obstacles in front of a technology and then wonder why it was not more widely applicable?

Answer: yes.

A brief nod to these obstacles is available up thread, to wit: “this guy KNOWS how long it takes a drug to reach the market.”

That length of time is not due to anything intrinsic to the biomedical R&D field. Scientists and engineers in the medical sector could ship products extremely rapidly if man-made obstacles were removed. Proof:

We issued an authorization for emergency use of a 2009 H1N1 diagnostic test within 24 hours of receiving an application and authorized an additional 17 diagnostic tests before the pandemic emergency was terminated. We also established an Office of Personalized Medicine with a talented staff who have already worked diligently to tackle some very difficult and thorny issues in personalized medicine.

In case that quote is not perfectly clear: when subject to political pressure, the FDA lickety split approved a new diagnostic test for H1N1 within 24 hours of receiving the application. When the man-made obstacle was taken out of the way, progress was rapid.

In the next few years, the US Government is going to go bankrupt and many agencies will shut down for good, just like the USSR fell from 1989-1991. Everyone knows that the USG is in trouble, but few realize how deep it goes (e.g. how many saw that the Fed printed not $787 billion, but rather $9 trillion)?

As a kind of “dry run” for USG collapse, you can read HHS’ plans for a government shutdown, where it indicates that about 99% of FDA officials will be indefinitely furloughed. The actual process of USG collapse will be a good deal messier, but count on them to use those shutdown plans to bring some order to the mayhem.

Now, the whole fall of USG will be VERY hard for many people.

But one silver lining is that genomics will be absolutely unleashed, with product cycles more along the lines of the 24 hour turnaround of the H1N1 diagnostic than the 5-10 year turnaround for the average 510(k) application.

In the next financial crisis, people with USD assets will be scrambling to eat and the funding for massive government agencies will not be there. What attention there is will be far away from the genome. Proof:

The FDA May Be Your Top Priority, But It’s Not Obama’s: There is a financial crisis under way, remember? “In this climate,” RPM writes, “priority goes to economic posts.” You know, the Securities and Exchange Commission and the Treasury Secretary. Besides, the Centers for Medicare & Medicaid Services is usually filled first. And as a post confirmed by the Senate, naming a new commish is guaranteed to take months. So let’s see, about 12 months from now…

Very few people today realize that the Internet of Google, Facebook, Amazon, etc. was only made possible when the government got out of the way and decriminalized commerce on the internet. Most just take it for granted that the internet is a place that allows extremely rapid development and deployment of new technologies with low input capital requirements. Few recognize that this is because the Internet has little if any regulation.

Similarly, very few people realize that the relatively slow advance of clinical genomics (and pharmaceuticals, etc.) is not due to physics but rather the FDA, exhibit A being that when the FDA got the political signal to get out of the way, a laboratory could take a diagnostic from research to market in 24 hours.

As with the internet, when genomics explodes in the years to come after USG’s collapse only a minority will realize that the fall-off in government power was the critical enabling step. No new equations necessary.

Do we really want to be handed a jumble of SNP risks without interpretation or responsibility for interpretation?

As to your Internet analogy, I still remember back in 2000 when PacBell sold me an unusable DSL “box” sans customer service. I could have bought cable, and should have, until the service and usability of the Internet had become reliable and cost worthy.

With personal genomics, for the time being, what is being sold is a set of possible SNP risks, with little understanding of how those risks translate into real early onset disease risk. And so far, what GWAS genomics reaffirms is that the genome is a highly complex multivariable system which needs to be exercised and appropriately nourished to run well. No drug can replace that.

As I’ve said before, it’s obvious that people will want their physicians to test them for very diseases once they are presented with a set of uninterpreted risks, real or not, from their personal genomic data. Those costs will be born by a health care system which most physicans will tell you must ration care in order to be cost effective. That’s true in both Canada, the US and Europe and is a reality of any healthcare system you can envision.

Taking your Internet analogy a little further, with deregulation, yes, we have gradually built a better Internet, but we also have poorer land line service, poorer quality of service, abusive telemarketing and polling, and less privacy. Many rural customers still do not have high speed Internet access.

As to the wonders of Internet deregulation, most of its fundamental technologies were researched prior to 1996, back in the day of telecommunications regulation including: the CMOS transistor, ARPANET, SONET, HTML, CDMA, CPRS, UMTS, optical transmission, the integrated superheterodyne receiver, integrated analog to digital conversion, and the touch screen character interpretation used in the iPhone.

Most Internet developments of the last ten years, including the iPhone, are developments which have built on the fundamental research of a more research friendly regulated world.

At its core, genomics today similarly requires fundamental research and an environment equivalent to institutions such as Bell Labs, CERN, and EPFL. As with Internet startups, some small r(esearch), big D(evelopment) will be possible through short term revenue generating prospects. However, I’m not sure that personal genomics will be one of them. And unless personal genomics can make people more healthy than a “measuring tape and a pair of running shoes,” we’re fooling ourselves as to its true cost-benefit.

Hi Daniel and all, I agree this discussion could go on forever! Maybe we should all meet up sometime? I also agree we do not disagree about everything. I do not think there was a conspiracy, but I do think there was a strong coincidence of interests. There is considerable evidence that the idea of genetic population screening (i) did gain considerable support from both the tobacco and food industries and others; and (ii) that this was used by leading scientists in the run up to the HGP to promote the idea to policy makers that there would be major public health gains and that there was industry support for this approach (even if their own personal interest was mainly just in doing the science); and (iii) population screening was widely advocated not least by the Blair government which e.g. proposed screening all or parts of the genome of every baby at birth (in the 2003 genetics white paper). Ronald Fisher wrote the additive model that does (certainly) over-estimate the genetic component of the variance of common diseases (although noone yet knows by how much: the problems may be very different for different diseases) AND went to work for the tobacco industry in the 1950s to promote the idea that lung cancer is caused by genetics not by smoking. Lots of public promises were made that this genetic approach to predicting and preventing common diseases would have a big impact on disease incidence and save money. This has let the food industry and others off the hook because it implies there is a technical solution that does not involve tackling our unhealthy food system in a much more fundamental way (and health inequalities etc etc). In other words, although I know you don’t see it this way, industry support for genetics research was partly used deliberately to undermine public health research and interventions. There is also plenty of evidence of companies selling gene tests that have nothing to do with the risks they claim to predict (some of which I helped expose). How is an ordinary person with no special training in genetics or statistics supposed to sift through all these (ofetn conficting claims) and make sense of them without the help of regulators? In reality, despite the sales pitch, we do not know the genetic risk of most diseases in most people (whether based on SNPs or whole genomes) and in most cases it’s really not that useful to inform decisions (you should go for that jog and skip that extra piece of cake anyway). This doesn’t mean we shouldn’t use the tests that are useful, or that there aren’t other useful aspects (e.g. understanding disease mechanisms or just furthering scientific knowledge). But this requires less hype and claim-making and more thoughful appraisal of what is known and unknown.

There is plenty of common ground and there is good and bad in all commerce.

Actually I think understanding better how genes and environment interact will help to expose the damaging effects of some “industrial food”. As long as there is no demonstrated explanation for why large groups of people seem to be immune to unhealthy lifestyles it will give the smoke and food industry the continued opportunity to spread doubt about the causes of harm. If we are able to involve genetics in precise explanations of the mechanisms of common disease development, far from letting them off the hook, it will more likely catch them red handed and give them nothing to hide behind anymore!

You are very right that there are elements in our society who would use genetics to distract people from major causes of ill health. Tabbacco is the clearest example of this, but by no means the only one. This is not unique to health either; you can also see the emphasis that certain sectors of society put on genetic causes of gender differences in technical ability, in order to avoid addressing the systemic societal factors that drive such inequality.

While genetics is one of the most obvious examples, the effect is by no means unique to genetic factors. Look at how the British right wing pushes obesity and lack of excerise, driven by laziness and a lack of discipline brough about by welfare payments, as causes of poor health amoungst the working class, in order to distract from the economic drivers of health inequality.

There are many elements of society who have an interest in marganalising health-impacting factors that do not sit well with their economic or political interests. Those of us have an interest in improving public health need to fight such people, be they people who claim that smoking doesn’t cause lung cancer, that genetics is the major driver of type 2 diabetes, that heart disease is caused by laziness, or that genetics does not contribute to complex disease.

Yep, that is exactly the point. The determinants of disease are what they are; finding the genetic determinants involved in disease *risk* (risk being a key concept here – genes are not “causes” but participants in a more complex set of biological processes where phenotypic disease is an endpoint) doesn’t let anyone off the hook because they do have the prospect of unpacking those biological processes. If we know the genetic “fixed points”, it allows us to investigate and perhaps modify the environmental variables to produce a better outcome. The GATTACA paradigm, for example, is known to be untrue – your genome does not predict everything about you. But it certainly does play a very major role in almost all disease processes, and knowledge of the genome is essential if we are going to make further progress (and we are making progress – very rapidly). But translating that into public health initiatives at a population level is not just a scientific challenge – it is a political and economic challenge too. Yet it still remains the case that we already know the best things people can do for their health – eat a bit less, exercise a bit more, cut out smoking, drink less alcohol. That doesn’t get us very far in terms of the biology however; we need the genes.

OK, Shane, Luke, it’s true that we need the genes, but do we need our own genes or just a reasonable facsimile?

I’d really like to see you guys discuss, straight on, the prospect and possible benefits of direct-to-consumer personal genomics versus a combined approach of genomic research, genetics informed public health initiatives and limited personal genetic testing based on family history and current state of health.

So much of the information put up on this site has been at the cutting edge of genetics. I can certainly see that genomics has a lot to offer people with disease risks where there are known methods of management. With management, knowing that you have a risk could allow you to push back the age of onset.

Still, most direct-to-consumer genetics customers will not be provided with the clear disease diagnosis and treatment possibilities that, for example, a Crohn’s sufferer would gain.

Most diseases (Alzheimer’s, heart disease, many cancers, type 2 diabetes) are at least partly delayed primarily through not smoking, exercising and maintaining a reasonably low BMI.

So why the heavy emphasis on direct-to-consumer genetics testing advocated by this site? I don’t get it.

Marnie, you make valid points; in my own defence (such as it is), I am not a fan of DTC genetic testing just for the heck of it, and I do think we are a long way off being able to translate (say) a personal exome into a meaningful risk figure that would make a difference to someone’s eventual outcomes. However I *am* very much in favour of much increased clinical use of genome sequencing for the actual management of patients and in research; the DTC stuff will ride on the coat-tails of that (or quite possibly vice versa!) – it’s unavoidable. And that being the case, I think it makes sense to look at ways of maximising the benefit of the DTC sector. The human genome project very much was the “reasonable facsimilie” you speak of, but in order to unpick the biology we need to know how differently-affected individuals riff on that theme. We need to look at a vast number of variants and correlate those as best we can with disease status – as I mentioned, this is all about unpicking the biology. And cheaper sequencing will continue to follow the demand, and that will spill over into the public realm simply as a function of reducing costs and increasing analytical capacity. We’re really only talking about 1.6gig of data (diploid, uncompressed) in your DNA – people will want that and people will get that.

As for why we this blog is so heavily about DTC genetics – this is a blog about personal genomics. We write about it because we think genetics is cool, and interesting, and looking at your own DNA to derive information about yourself, be it health, ancestry, genealology or just ear-wax type, is awesome, regardless of clinical utility. A world where people are aware of and engaged with their own genetic data is a better one, just like a world with the printing press in was, and screening implications of DTC genetics are only a tiny little part of that.

As for the direct use of universal genetic testing, no-one here has suggested that we should just start screening everyone for all diseases based on this data. In fact, in my opinion, the way we handle low-impact personal risk of any kind in our system makes this unlikely to be helpful. An emphasis on disease over wellness, of treatment over prevention, of drugs over lifestyle management, and of paternalism over informed self-determination, doesn’t really fit sit well with screening based on low-to-moderately-predictive factors – what are you going to do, run an MRI of everyone above 40% and prophylactically treat the top 20% with an expensive drug?

I would see DTC genomics as a way of moving away from our current paradigm (which is why I am uneasy about the FDA makign genetics just another test that you can only get from your doctor). In that context, being aware of what phenotypes you and your family are more prone to (even very mildly), can change behaviours, if each individual can be informed about the sum total of their risks, and can access this information themselves, in an easy-to-interpret way. Genetics is just a small part of such a shift in thinking, but it is a very useful testing ground. It allows people to think as health as personal information about them, something that is theirs, rather than something that is done to them by others.

As an example: just like an LDL of 4.2 means something different (and suggest different causes of action) if you are lean vs if you are overweight, it’ll also mean something different depending on your metabolic-associated variants and your metabolic disease risk: this combined set of factors will suggest whether you should just get more exercise and eat less bacon, whether you should enrol in a proscribed exercise program and keep a food diary, whether you should also consider additional screening for metabolic disorders, and whether you should consider a pharmaceutical intervention. A doctor is likely to just put you on statins, or tell you not to worry, without considering the evirnoment, lifestyle or genetic situation you are in – most doctors, with the current frameworks we use, just doesn’t have the resources or the expertise to tailor advice based on these fine-scale differences. Likewise, most patients do not have access to the information to make their own decisions. However, if they did, then people could make their own decisions, based on the sum total of their risk factors.

Can people interpret this sum-total-of-risks information? Well, not if you give them a big sheet of numbers, but a lot of people (not least the DTC genetics companies themselves) have been putting a lot of work into how we can visualise this information, and communicate it in a way that gets across the magnitude of risk. Will they use it? We need to get them to, because individuals need to take charge of their own health to avoid the spiraling health-care costs and health-care inequality that’ll come when we try and apply the current paradigm to a growing, aging worlwide population.

I’d really like to see you guys discuss, straight on, the prospect and possible benefits of direct-to-consumer personal genomics versus a combined approach of genomic research, genetics informed public health initiatives and limited personal genetic testing based on family history and current state of health.

I simply don’t see this as a “versus” issue: personal genomics will not (and should not) displace other efforts to integrate genetic information into healthcare. Our goal here is not to advocate that DTC companies replace clinicians, but simply to point out that these companies are (1) a valuable source of innovation in the display of complex genetic risk data to non-experts; and (2) a welcome step in the direction of empowering individuals to take greater responsibility for their own healthcare.

Right now, the technology and science are not at the stage that personal genomics provides much useful health-relevant information to most users (although there are exceptions – I hope Luke will discuss his own experiences in this area soon). But the field is moving fast, and as we get cheaper sequencing and better functional annotation of the genome, we’ll need to be ready to ensure that motivated individuals can take full advantage of it. Right now, personal genomics companies are doing a better job than anyone else of building the infrastructure to allow that to happen – and they should be encouraged to keep doing it.

there should be no “versus”. It is not Genetics vs. family history or genetics vs. traditional risk factors. they are all in there together.

Real clinical utility in genome scans is scarce at the moment, but not absent as Daniel alludes to. Many are underwhelmed by their results – of course because most people are close to the average risks… I’m happy to be quite unexcited by my APOE and carrier results for example

But it will become more and more relevant (and cheaper) – it would be a better idea for the medics ecc to embrace rather than try and push it away

That’s a good point; a lot of the resistance among medics (speaking as a medic!) is down to the delusion that we can perhaps control this in the new world of widely-available genetic technology. I am very much anticipating the day, not very far away, when the parents of, say, a syndromic child pitch up in my clinic with the child’s genome sequence on a memory stick. I don’t see any way we can (?should) prevent this, and ignoring it is not an option, so we’re going to have to deal with it and as Keith says, embrace it. What I would rather *not* see is a flood of “worried well” getting referred to clinical services because of mildly elevated risks for one thing or another, picked up by personally-initiated DTC tests. I’m not convinced we know yet how to deal with that issue, but it’ll not be by restricting people’s access to their own genetic information.

-I hope we can avoid the kinds of fearful discussions you see coming up now on some wiki SNP pages. Many people seem ill prepared to interpret the information they are currently being handed by DTC companies.

-I believe that most of us would likely prefer to be discussing our genomic information with a healthcare professional with a background in internal medecine and genetics and not some DTC genetics helpline dweeb with little responsibility or ability to discuss risk or make a referral.

-In the US, health insurance companies have already shown that they will attempt to drop patients from their policies if they know that a patient has a high risk for an expensive to treat disease. It will be very difficult to stop that. Most people will not have the ability to take on the all powerful US health insurers.

-Some people with DTC data will attempt to gain access to expensive healthcare. The person with the fluttering heart valve SNP will all of a sudden want an ECG, people with high breast cancer risk will want prophylactic mastectomy and reconstruction, people with heart disease risk will increasingly ask for expensive prophylactic drug prescriptions, etc. Many will arrive in their doctors offices saying that they simply have a family history of this or that and will not mention that their concerns are driven by a DTC result. The doctor will have to run a number of tests and sometimes will write the prescription for the prophylactic test. Costs will go up. Sooner or later, insurance companies will catch on and will start to push back. It’s going to be a rough ride for all of us.

Just a few things to think about. I hope the FDA is thinking about this.

On the plus side, it’s great to hear about the attempts to better visualize DTC genomic information. That will be helpful to doctors, DTC genomics companies and the public.

I’d also say that at least in some medical practices, limited use of genomics information is already being used toward preventive care. See “Cardiovascular Disease: Revolutionizing Treatment and Prevention”

I believe that most of us would likely prefer to be discussing our genomic information with a healthcare professional with a background in internal medecine and genetics and not some DTC genetics helpline dweeb with little responsibility or ability to discuss risk or make a referral.

Sure, that would be great. But given there are about fourteen clinicians in the US with the ability to knowledgeably discuss the results of a genome scan, that’s not going to happen: you’re presenting a false choice.

In fact, your real choice right now is more stark: get your results from a company that has invested heavily in building up a comprehensive database of genetic associations and an intuitive interface, or discuss your results with a primary physician who doesn’t know what a SNP or an odds ratio is. Ban DTC, and you’re forced to choose the latter.

In the US, health insurance companies have already shown that they will attempt to drop patients from their policies if they know that a patient has a high risk for an expensive to treat disease. It will be very difficult to stop that. Most people will not have the ability to take on the all powerful US health insurers.

Right. We need to make a choice: either allow insurance companies to use genetic information (in which case some people will pay higher premiums due to their genomes, or be ineligible for insurance), or allow the private insurance industry to die. As genetic information becomes more predictive, the insurance industry will not survive a massive imbalance between the risk information its customers have access to and what it can use in calculating premiums.

Either way, the outcome is the same: some form of socialised healthcare will be needed as we enter the era of genomic medicine. There is no way around this.

Some people with DTC data will attempt to gain access to expensive healthcare. The person with the fluttering heart valve SNP will all of a sudden want an ECG, people with high breast cancer risk will want prophylactic mastectomy and reconstruction, people with heart disease risk will increasingly ask for expensive prophylactic drug prescriptions, etc. Many will arrive in their doctors offices saying that they simply have a family history of this or that and will not mention that their concerns are driven by a DTC result.

*shrug* And some tiny fraction of people will arrive at their doctor lying about a family history of a disease, when actually they just read about it on WebMD and are sure they have the symptoms. You can’t legislate to stop people lying to their doctors.

More commonly, people will come to their doctors honestly discussing their concerns about their DTC genomics results, and asking what they should do about them. In some fraction of cases the doctors will order unnecessary tests as a result. That’s bad. But this isn’t a problem with DTC genomics: it’s a failure of clinicians to weigh up evidence to make appropriate clinical decisions. The solution isn’t to ban DTC – it’s to educate clinicians.

The only thing is that the DTC company may well present you with risks that are pretty accurate, but not (generally) with a pathway to streamline your healthcare access, should you need it. But if a situation is unavoidable, the response has to be to manage it, not pretend that it can be dodged.

Ironic, therefore, that in the UK our government seems determined to dismantle the National Health Service, which is precisely the sort of jalopy we should be souping up to take the genomic revolution forward into individualised care. I must dig out that old House of Lords report that came out a while back; even only a couple of years later it is beginning to look *very* dated…

“Sure, that would be great. But given there are about fourteen clinicians in the US with the ability to knowledgeably discuss the results of a genome scan, that’s not going to happen: you’re presenting a false choice.”

@Daniel

At least in the Bay Area, many doctors are increasingly deploying genetics to treat their patients. They may not be able to interpret a whole genome test, but pre-natal CVS testing across an array of genetics risks is widely available, as is testing for various heart and diabetes risks. You’re under estimating the ability of the medical profession to deploy genomics information to treat their patients.

I’m not at all confident that patients who are diagnosed with a high risk for genetic illnesses will be able to get care in the US. We already have whole classes of patients in the US who get very minimal care. The secondary system, Medicare, that has traditionally helped these patients, is crumbling. We’ve already voted down the public option. The private insurance companies will not die, but many people who are lopped off from health care, due to a diagnosis of high genetic risk, will.

You’re under estimating the ability of the medical profession to deploy genomics information to treat their patients.

I’ve spoken to plenty of clinicians about genomics. There are some notable exceptions, but almost none of them would be prepared to explain complex genetic disease risk prediction a fraction of a percent as well as 23andMe does.

That will change, or at least I hope so. But in the meantime, insisting that we should all access our genome interpretation via a group of people who are patently unqualified to do so is absurd.

I’m not at all confident that patients who are diagnosed with a high risk for genetic illnesses will be able to get care in the US.

I’m not confident either – but we’re both just going to have to wait and see.

it’s going to be interesting to watch – there will be all sorts of situations to sort out and I expect it will be messy. I think Daniel is right about the death of insurance, it’s also something Paul Nurse said back in 2003, so that’s good company! But it will be a long chronic ilness & not a sudden death.

There will be all sorts of ethical questions like if I am told that by following a certain lifestyle, I will not get diabetes then maybe the insurers, or society, would be right to “punish” me if I do get diabetes through ignoring the advice.

Right now in many cases according to quite a few studies, diet and excercise can be more effective at reversing high cholesterol than statins can, and can me more effective at reversing high glucose & “pre diabetes” than metformin can. If that is so, should it piss me off that some of my tax euros are being used to pay for life long statin medication that could be avoided? At least the smoker more or less pays his bill in cigarette taxes.

As for doctors – they are not perhaps the best people to interpret this sort of personal genetics in any case. Their idea of “prevention” is tackling raised risk factors with medication, or expensive screening. Fair enough, they did not study for 10 years to deal out diet and lifestyle advice to not ill people. It’s more of an opportunity for other sectors: nurses, biologists, dieticians, pharmacists, etc

If there really are risks of not having access to healthcare due to a genetic diagnosis, then surely well people who are aware of this will not pay 23andme to take on this risk.

I’m in that category. My family history doesn’t indicate any looming unusual genetic illnesses. I’m able to make use of general health information to direct preventive choices. I’m in good health and am able to exercise. There’s really little upside for me to fork my genome over too 23andme.

Yes, genetics is cool, but as you point out, most people of British Isles descent are related at the level of about sixth cousins. So a sample of less than 10,000 people of British Isles descent should be plenty to estimate disease risk for me.

According to that recent paper, people of other ancestries are even more related than Western Europeans. So no need for huge sample sizes.

Meanwhile, I’ll keep my genome under wraps and head out for a walk. However, I will still eat chocolate.

There is another possible outcome that would not mean the end of insurance, after all, the goal of personal genetics is to keep us healthy for longer. If we achieve high levels of accuracy in predicition for the majority of diseases it will not be “you will get cancer, diabetes or whatever – the predicition will always be conditional on lifestyle choices. So in the best scenario the forecast will be “you will almost certainly develop diabetes in middle age if you do this and don’t do that”.

Then it all depends on what the reaction will be – will “almost certain if…” cause us to choose to follow lifestyles compatible with long term good heath? If it does then we should get cheaper insurance if we get tested – if we don’t… then we deserve whatever will happen.

WTCCC1 in mid-2007 was not the first GWAS. That shows the authors to be rather ignorant.

FWIW, they used the Affymetrix 500k, and both Affymetrix and Illumina started their commercial products in the ~10k SNPs range. People has been using that and publishing researches, some of them quite successfully, before WTCCC1, for years.

You are right that WTCCC1 was not the first GWAS paper (that honor probably goes to Klein et al). Not sure how that error got in, certainly those of us who work in GWAS are aware of the pre-CCC1 GWAS efforts!

However, I am not aware of any successful GWAS using the ~10K linkage mapping chips. Are you sure you aren’t thinking of linkage scans?

No as I just said Klein et al AMD GWAS (which used the Affy 100K) was the first successful GWAS published.

WTCCC1 is often thought of as the birth of the modern GWAS, as it was the first to be (relatively) well powered and have (relatively) complete genome-wide coverage. It was the first time that thousands of cases were genotyped per disease, and was thus the “definitive” first look at the 7 diseases it studied.

We tried a little proof of principle a few years ago, when the chips were still expensive. We carefully pooled DNA from a number of different patient cohorts (including AMD) – about 20 cohorts in total, each with >50 patients (if my memory serves me right!), then ran the pools on 20 separate arrays. Using this technique alone, and very cheaply, we were able to show a strong signal from the CFH locus using a rough-and-ready stats analysis that we cooked up on the hoof (mainly involving Excel manipulation). In the end, events ran ahead and we never published the technique; we felt it was at best suitable for very low-hanging fruit that we would then verify individually. Although it suggested a few candidates for other conditions, none of these turned out to be real when we went back and did the individual genotyping. But a fun pit-stop all the same.

Yes I know :-) I’ll see if I can dig out some of our old files and show you what we did next time I’m over at the Sanger. It’s not really that relevant nowadays, but it was a bit of fun. And certainly not well-enough nailed down to publish in a reputable journal!

Dear Genomes Unzipped, I like the website content and organization- it is great to have so many inputs to the discussion, and also your curated take on things.

I am writing because I have a rebuttal to one of the main contentions about the benefits of GWAS, which appears to be something that is “unquestionable”. I disagree with this unquestionable-ness, and and I’m interested to hear things from your point of view on this. The point that I disagree with is the assertion that, while GWAS often has poor predictive value, it still can offer important insights into disease mechanism. As you are well aware, the poster child for GWAS is age-related macular degeneration (AMD). I cannot speak for Crohn’s dz, but because of my analysis of the situation for AMD, I am a little bit skeptical of the claim there, too.

It is simply counterfactual to say that GWAS gave AMD researchers a better understanding of disease pathogenesis for several reasons.

First, you can see for yourself in the following references that there was a rather strong interest in the role of complement proteins in AMD well before the GWAS findings of 2005:

Second, the failure of all of several recent clinical trials that have attempted to therapeutically inhibit complement activation should give everyone caution as to whether this is a viable treatment strategy. These have been in the form of intraocular or intravenous injections with various compounds… all avenues have been unsuccessful.

Finally, preclinical and human data hardly support the claim that complement is the, or even a, main driver of AMD pathogenesis.